Bottomland hardwoods are among the most diverse and productive forest ecosystems in the southeastern United States and are critically important for the provision of timber and non-timber ecosystem services. Red oaks, the dominant species in this group of forests, are of high ecological and economic value. Stem profile models are essential for accurately estimating the merchantable volume of oak trees, which is also closely indicative of total tree biomass and other ecosystem services given their allometric relationships. This study aims to develop and compare stem profiles among three red oak species in an 18-year old plantation forest using destructive sampling. Sixty trees randomly selected from an oak restoration plantation in the Arkansas Delta were felled for measuring the diameter-outside-bark (DOB) and diameter-inside-bark (DIB) at different stem heights. These sample composed of twenty trees from each of three species: cherry bark oak (CBO - Quercus pagoda Raf), Nuttall oak (NUT - Quercus texana Buckley), and Shumard oak (SHU - Quercus shumardii Buckl). Multiple models, including the segmented-profile model, form-class profile model, and second-and third-order polynomial models were fitted and compared. Results demonstrate that the form-class profile model was the best fitted for CBO and NUT, whereas the third-order polynomial model was the best for SHU. CBO tends to grow taller and has a higher wood density than NUT and SHU. These findings will inform restoration and management decisions of bottomland hardwood forests, especially red oaks in the region.
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Citation
Tian N, Gan J, Pelkki M (2022). Stem profile of red oaks in a bottomland hardwood restoration plantation forest in the Arkansas Delta (USA). iForest 15: 179-186. - doi: 10.3832/ifor4057-015
Academic Editor
Agostino Ferrara
Paper history
Received: Jan 05, 2022
Accepted: Apr 05, 2022
First online: May 19, 2022
Publication Date: Jun 30, 2022
Publication Time: 1.47 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2022
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This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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